Channel estimation in a cellular communication system

ABSTRACT

A method of channel estimation in a cellular communication system is described. Symbols are transmitted between a mobile station and a base station. According to the described method, an incoming signal is received via a communication channel. A first estimate for the channel impulse response of that communication channel is provided and used to process the incoming signal to generate an estimated data symbol. The estimated data symbol is used to generate a soft output feedback decision which is then used to make a further estimate of the channel impulse response.  
     According to a variation, the further estimate of channel impulse response is made by performing a correlation process between a conjugate version of a spreading code used to spread the incoming signal and the incoming signal itself. The results of that process are multiplied by a feedback decision.

[0001] The present invention relates to a method and circuitry forchannel estimation in a cellular communication system.

[0002] The invention is particularly concerned with a cellularcommunication system in which data is transmitted as a plurality of datasymbols over a sequence of time slots. As is known, in a CDMA system,data is encoded for transmission by modulating data symbols to betransmitted by a unique spreading code for each of a plurality ofcommunication channels. Within each cell of a cellular communicationsystem, spreading codes allow for a plurality of different mobilestations to communicate with a base station on selectively codedchannels.

[0003] When a signal is transmitted between a base station and a mobilestation (either on the uplink or the downlink), the signal receivingunit needs to establish from the signal which it has received someinformation about the communication path along which the signal hastravelled. This is referred to herein as “channel estimation” andis/carried out in a channel estimation unit which generates a channelimpulse response. Various techniques are known for channel estimation.The channel impulse response is required in order to properly decode anddemodulate incoming data.

[0004] In an earlier proposed CDMA system explained in the TechnicalReport of IEICE (1996-02) entitled “Variable Rate Data Transmission onSingle Code Channels in DS/CDMA” by Okomura et al, data is transmittedat variable transmission rates. Channel estimation is carried out frompilot symbols spaced periodically in the data stream.

[0005] One difficulty associated with this proposal is that only theenergy from the pilot symbols is available for channel estimation, andthe signal to noise ratio of pilot symbols tends to be poor. Thus,filtering is required to get more reliable estimates. In particular, inthe case of mobile stations moving at high speeds, it may be difficultto apply a suitable filtering technique due to short channel coherencetime.

[0006] It is therefore advantageous to use data symbols in addition tothe pilot symbols for channel estimation. The present invention seeks toprovide a technique for improving channel estimation using estimateddata symbols.

[0007] According to one aspect of the invention there is provided amethod of channel estimation in a cellular communication system in whichsymbols are transmitted between a mobile station and a base station, themethod comprising:

[0008] receiving via a communication channel an incoming signal;

[0009] providing a first estimate for the channel impulse response ofthat communication channel and utilising that first estimate to processthe incoming signal to generate an estimated data symbol;

[0010] using said estimated data symbol to generate a soft outputfeedback decision; and

[0011] using the soft output/feedback decision to make a furtherestimate of the channel impulse response.

[0012] The invention is particularly but not exclusively applicable to aCDMA system in which the incoming signal incorporates symbols spread bya spreading code.

[0013] According to another aspect of the invention there is provided amethod of channel estimation in a cellular communication system in whichsymbols are transmitted between a mobile station and a base station, themethod comprising:

[0014] receiving via a communication channel an incoming signal whichincorporates symbols spread by a spreading code;

[0015] providing a first estimate for the channel impulse response ofthat communication channel and utilising that first estimate to processthe incoming signal to generate an estimated data symbol;

[0016] making a further estimate of the channel impulse response byperforming a correlation process between a conjugate version of thespreading code and the incoming signal, and multiplying the results ofthat process by a feedback decision based on said estimated data symbolas a weighting value for the further estimate of the channel impulseresponse.

[0017] The incoming signal can include data symbols and pilot symbols,with a unique spreading code having been used respectively for pilotsymbols and data symbols.

[0018] According to the further aspect of the invention, the feedbackdecision may be a soft output or a hard output.

[0019] A further aspect of the invention provides circuitry forestimating a channel impulse response in a cellular communication systemin which symbols are transmitted between a mobile station and a basestation, the circuitry comprising:

[0020] a receiver for receiving via a communication channel an in comingsignal which incorporates symbols spread by a spreading code;

[0021] a channel impulse response generator for providing a firstestimate for the channel impulse response of that communication channel;

[0022] a data symbol generator for generating an estimated data symbolusing the first estimate of the channel impulse response;

[0023] circuitry for providing a further estimate of the channel impulseresponse by performing a correlation process between a conjugate versionof the spreading code and the incoming signal, and multiplying theresults of that process by a feedback decision based on said estimateddata symbol as a weighting value for the further estimate of the channelimpulse response.

[0024] A still further aspect of the present invention providescircuitry for estimating a channel in a cellular communication system inwhich symbols are transmitted between a mobile station and a basestation, the circuitry comprising:

[0025] a receiver for receiving an incoming signal via a communicationchannel;

[0026] a channel impulse response generator for providing a firstestimate for the channel impulse response of that communication channel;

[0027] a data symbols generator for generating an estimated data symbolusing that first estimate;

[0028] a soft output feedback decision generator for using saidestimated data symbol to generate a soft output feedback decision;

[0029] wherein the soft output feedback decision is used to make afurther estimate of the channel impulse response.

[0030] The invention also contemplates a base station and/or a mobilestation incorporating circuitry according to the first aspects of theinvention.

[0031] For a better understanding of the present invention and to showhow the same may be carried into effect, reference will now be made byway of example to the accompanying drawings in which:

[0032]FIG. 1 is a block diagram illustrating schematically symbolestimation in a basic CDMA system;

[0033]FIG. 2 is a block diagram illustrating a cellular communicationsystem;

[0034]FIG. 3 is a diagram illustrating a transmission time slotstructure;

[0035]FIG. 4 is a block diagram illustrating channel estimation withfeedback;

[0036]FIG. 5 is a block diagram of circuitry in a channel impulseresponse unit;

[0037]FIG. 6 is a vector space diagram; and

[0038]FIGS. 7 and 8 are simulations of acquisition probability againstsignal energy per bit to noise ratio.

[0039]FIG. 1 is a block diagram of a basic receiving system in a CDMAcellular communication network. FIG. 2 is a block diagram illustrating acontext in which the present invention may be used. That is, a CDMAmobile communication system allows a plurality of mobile stations MS1,MS2, MS3 to communication with a base station BTS in a common cell viaRF signals on respective channels CH1, CH2, CH3. These channels aredistinguished from one another by the use of spreading codes in a mannerwhich is known per se.

[0040] Reverting now to FIG. 1, signals incoming at an antenna 30 arereceived by an RF unit 28 and supplied to an analogue-to-digital (A/D)converter 32. The A/D converter takes samples of the incoming signals atintervals i to generate digital sampled values x. It will readily beunderstood that a signal may arrive at the receiving circuitry havingexperienced multi-paths with differing propagation delays. Each digitalsampled value x_(i) may include therefore components of a number ofdifferent symbols depending on the multipath effect.

[0041] The digital signal is supplied from the A/D converter 32 to achannel impulse response unit 37 which provides an estimated channelimpulse response H for use in processing the incoming signal. Areference code generator 22 supplies a reference code for despreadingthe incoming signal both to the channel impulse response unit 37 and toa rake receiver 36. The reference code is denoted C and is the uniquespreading code for the communication channel on which the signal isreceived. Thus, it matches the code which was used to spread the signalprior to transmission at the base station or mobile stationrespectively. Although FIG. 1 illustrates circuitry located at eachmobile station, similar circuitry may also be utilised at a basestation.

[0042] The rake receiver 36 additionally receives the input digitalsignal x and the estimated channel impulse response H. It generates anestimated transmitted signal u which is supplied to a decoder 31. Thedecoder estimates symbol values s from the estimated signal u which hasbeen derived from the actual incoming signal x, in a manner which isknow per se.

[0043] Operation of the rake receiver is known to a person skilled inthe art but in any event is described in more detail in ApplicationWO96/24988 in the name of Nokia Mobile Phones Limited.

[0044] The form in which data is transmitted is illustrated by way ofexample in FIG. 3. The data symbols are transmitted in a sequence oftime slots, each time slot including pilot symbols (PS) and coded data.Data is transmitted as a set of analogue symbols which are produced fromoriginating digital data by i,q modulation. In a CDMA system the symbolsare spread by a spreading code prior to transmission. In a typicalsystem, each time slot has a duration of 0.625 ms. The pilot symbols areintroduced at the beginning and end of each time slot in a coherentsystem. These symbols are readily recognisable and so the beginning andend of each time slot can be identified for synchronisation purposes. Inthe circuit of FIG. 1, the pilot symbols are additionally identified andused in the estimation of the channel impulse response by the channelimpulse response 37.

[0045]FIG. 4 illustrates an improved version of the circuitry of FIG. 1.In FIG. 4, the estimated symbol s is fed back to the channel impulseresponse unit 37 via a feedback decision generator 20 which generates afeedback decision D from the estimated symbol s. That feedback decisionD is used to improve the estimate of channel impulse response generatedby the CIR unit 37. An SIR block 29 receives the incoming signal samplesx and the estimated signal u and calculates the signal to informationratio used to generate noise variance σ² for the feedback decisiongenerator 20.

[0046]FIG. 5 illustrates how the feedback decision D is used to improvethe estimated channel impulse response. FIG. 5 illustrates a CIR unit 37which is capable of providing an estimated channel impulse response Husing both fedback estimated data symbols and incoming pilot symbols.The circuit comprises first and second matched filters 10,12 which areeach used to apply the relevant despreading code to the incoming digitalsignal x_(in). The reference code generator 22 generates three codes. Aspreading long code LC is applied to both of the match filters 10,12. Aspreading short code W_(p) for pilot symbols is applied only to thefirst match filter 10 and a spreading short code W_(d) for data isapplied only to the second match filter 12. The output signals 14,16From the first and second match filters 10,12 respectively are appliedto an averaging circuit 18. The averaging circuit receives the decisionfeedback D and applies that to the signals 14,16 from the matchedfilters to generate the estimated impulse response H.

[0047] The averaging circuit 18 includes a memory 40 for holdingprevious channel impulse responses and a weighting/averaging unit 42 fortaking an average of the earlier channel impulse responses and applyinga weighting function according to the fedback decision value D.

[0048] The correlation process which is used to establish the estimateof channel impulse response can be expressed as: $\begin{matrix}{{H_{n}(t)} = {{\sum\limits_{i}{{D_{n} \cdot {C^{*}(i)}}{x\left( {i + t} \right)}}} = {D_{n}{\sum\limits_{i}{{C^{*}(i)}{x\left( {i + t} \right)}}}}}} & \left( {{Equation}\quad 1} \right)\end{matrix}$

[0049] In the above equation, i is the sampling time index along thereceived signal, t is the resulting sampling time index of thecorrelation process, x(i+t) is the received data sample for that index,C* is the conjugate of the spreading code and D_(n) is the n_(th)decision feedback where n is the time index of the impulse response. Itwill be apparent that the decision feedback D may be in respect of pilotsymbols and/or data symbols.

[0050] In use, an initial estimate for the channel impulse response Hwould be established by the CIR unit 37 on the basis only of knownincoming pilot symbols in a particular time slot in a manner which isknown per se. Alternatively, an initial estimate can be made usingEquation (1) without the weighting function D. Once a preliminaryestimate of the channel impulse response has been established, this isheld in the memory 40 and supplied to the rake receiver 36 forsubsequent signal processing of data symbols in that time slot. Thefirst data symbol to be estimated is then subject to feedback to providea feedback decision D so that a new estimate for the channel impulseresponse H can be determined using the procedure outlined above and asillustrated in FIG. 5. The spreading code conjugate C* in equation 1 isderived from merging the conjugates of W_(d) and LC (for data) or W_(p)and LC (for pilot symbols). Then, an average is taken of the newestimate and the preliminary estimate. Thus, at each estimated symbol animproved channel impulse response is obtained for subsequent processing.The average can be taken coherently within any coherent period, that ispart of a slot, one whole slot or a multiple of slots. Alternatively, anon-coherent average can be taken over any period.

[0051] It will be apparent from Equation 1 that the correlation processcan effectively be implemented without decision feedback as if all thetransmitted data symbols are ones. The transmission feedback D acts asan average weighting factor to determine the estimated channel impulseresponse H.

[0052] Another aspect of the implementation discussed herein is todetermine the nature of the decision feedback D generated by thefeedback decision generator 20. FIG. 6 illustrates the theory underlyingone proposal which is to utilise a soft symbol decision feedback (SDFB)process by generating a soft feedback decision value D. FIG. 6illustrates a vector diagram of signal space. Vector A is a transmitteddata signal. Vector A′ is the received data. Vector A is the actualvalue we expect from the transmitted data signal since the rake receivercannot be perfect. The received data symbol can be written as:

A′=a+n  (Equation 2)

[0053] where n is the noise vector.

[0054] It is natural to assume that both the signal and the noise arezero mean. We have: $\begin{matrix}\begin{matrix}{{E\left\{ a \right\}} = 0} \\{{E\left\{ n \right\}} = 0} \\{{E\left\{ A^{\prime} \right\}} = {{E\left\{ {a + n} \right\}} = 0}}\end{matrix} & \left( {{Equation}\quad 3} \right)\end{matrix}$

[0055] In a binary (+1/−1) environment, we have also: $\begin{matrix}{{{E\left\{ {A\quad A^{*}} \right\}} = 1}\begin{matrix}{{E\left\{ {A^{\prime}{A^{\prime}}^{*}} \right\}} = {E\left\{ {\left( {a + n} \right)\left( {a + n} \right)^{*}} \right)}} \\{= {{E\left\{ {a\quad a^{*}} \right\}} + {E\left\{ {n\quad n^{*}} \right\}}}} \\{= {{E\left\{ {a\quad a^{*}} \right\}} + \sigma^{2}}}\end{matrix}} & \left( {{Equation}\quad 4} \right)\end{matrix}$

[0056] where σ² is the noise variance.

[0057] With these statistics of the signal, the soft output can beadjusted to satisfy the conditions for feedback if the noise variance isknown beforehand. For a simple solution, we suppose that the signal lossis minimum and can be neglected:

|a−A|→0

[0058] Then equation (3) becomes: $\begin{matrix}\begin{matrix}{{E\left\{ {A^{\prime}{A^{\prime}}^{*}} \right\}} = {{E\left\{ {a\quad a^{*}} \right\}} + \sigma^{2}}} \\{= {{E\left\{ {A\quad A^{*}} \right\}} + \sigma^{2}}} \\{= {1 + \sigma^{2}}}\end{matrix} & \left( {{Equation}\quad 5} \right)\end{matrix}$

[0059] Using this analysis, the feedback decision generator can generatea soft value D satisfying the following requirements:

E{D}=0  (Equation 6)

E{DD*}·=1+σ²  (Equation 7)

[0060] As an alternative, a hard decision feedback may be utilised byperforming a binary cut-off, that is to provide either +1 or −1 to theinput of the channel impulse response unit for each estimated symbol S.

[0061] The effectiveness of both solutions is illustrated in FIGS. 7 and8. In FIGS. 7 and 8, the x axis represents signal energy per bit tonoise ratio (E_(b)/N_(o)) and the y axis represents the scale ofacquisition probability—that is the likelihood that all signalpropagation paths have been captured in the received signal as estimatedusing the C.I.R. FIG. 7 is the simulation results with the best possiblechannel estimation, and FIG. 8 is the simulation results in which thechannel information of a slot is obtained only from the pilot symbols inthe same slot. These simulations have been generated based on the MATLABprogram included as Annexe 1. The simulation results compare theacquisition probabilities of the impulse response of differentapproaches of the decision feedback compared with no decision feedback.In both cases, it can be seen that the best results are given by a softdecision feedback for both pilot and data symbols. This is the top/linein both simulations. The next line is for soft feedback decisionsrelating only to data symbols, that is without pilot symbol feedbackbeing taken into account.

[0062] The next line is for hard data feedback decisions in respect ofdata symbols only.

[0063] The lowest line is where there is no decision feedback. ANNEXE 1MATLAB program % Soft Decision Feedback % ARIB specification % QZD/NTC -FEB.98 - Oulu clear, rand(‘seed’,0), randn(‘seed’,0) Dat_Weight = 0.5;SNR = −30:3:0; Fingers = 10;h=[0.7+j*0.1,0,0,0,−0.5−j*0.3,0,0,0,0,0.3+j*0.5,0,0, ... 0.1−j*0.13,0,0,0,0,0,0,0.3−j*0.1,0,0,0,0.5+j*0.5, ... 0,0,0,−0.5−j*0.3,0,0,0,0,0.3+j*0.5,0,0,0.1−j*0.13,... 0,0,0,0,0,0,0.3−j*0.1]; h=h/sqrt(h*h′); AcqError = zeros(size(SNR,2),4); for kkk = 1:size(SNR,2) snr = SNR(kkk)  % SNR in dB   for nnn=1:1000DAT = (rand(1,40)>0.5)*2−1; % CODE CL_I=(rand(1,2560)>0.5)*2−1;CL_Q=(rand(1,2560)>0.5)*2−1; C = CL_I + j*CL_Q; w=1;for k=1:6;w=[w w;w−w];end;w0=w(1,:);w1=w(2,:);clear w; W0=[ ];W1=[ ]; for k=1:40,W0=[W0,w0];W1=[W1,w1];end C0 = w0 .*C; C1 = W1 .*C; % Spreading D=[ ];for k=1:40, D−[D,DAT(k)*w1];end % Data P=ones(size(D));             %PILOT X1 = (D + j*P) .* C; % Channel x2 = conv(x1,h)/2; % NoisenA=1/10{circumflex over( )}(snr/20);fork=1:size(x2,2);n(k)=nA*randn*exp(j*rand*2*pi);end x =x2 + n; %%%%%%%%%%%%%%%%%%% MF %%%%%%%%%%%%%%%%%%% IRPilot = zeros(39,64); IRData = zeros(39, 64); for k=1:39, 1=(k−1)*64;  for m = 1:64  IRPilot(k,m) = IRPilot(k,m) + x(1+m−1+(1:64))*C0(1:64))′;  IRData(k,m) = IRData(k,m) + x(1+m−1+(1:64))*C1(1:64))′;  end endIRPilot = −j*IRPilot/64; IRPilotHard=sum(IRPilot(1:28,:))/28; IRData =IRData/64; %%%%%%%%%%%%%%%%%%% H′%%%%%%%%%%%%%%%%%%%%%%%%%% a =IRPilotHard .* conj(IRPilotHard); H = zeros(size(h)); for k = 1:Fingers,findf = 0;  while( findf < 1)   [n,m]=max(a); a(m)=0;   if(m<=size(h,2)), H(m)=IRPilotHard(m); findf=2; end  end end%%%%%%%%%%%%%%%%%%% decision %%%%%%%%%%%%%%%%%%% h1=find(abs(h)>0.01);h2=h1;         % Idea %h2=find(abs(H)>0.01); % blind PilotSoft =zeros(1,28); DataSoft = zeros(1,40); for n=1:Fingers a =x(h2(n):size(C0,2)+h2(n)−1) .* conj(C0) * conj(H(h2(n)));  for k=1:28  PilotSoft(k) = PilotSoft(k) + imag(sum(a((k−1)*64+1:k*64)));  end a =x(h2(n):size(C1,2)+h2(n)−1) .* conj(C1) * conj(H(h2(n)));  for k=1:40  DataSoft(k) = DataSoft(k) + real(sum(a((k−1)*64+1:k*64)));  end endPilotSoft = PilotSoft/64; DataSoft = DataSoft/64; DataHard =sign(DataSoft); %%%%%%%%%%%%%%%%%%% Averaging %%%%%%%%%%%%%%%%%%% a = 0;b = 0; c = 0; IRHard=zeros(1,64); IRSoft=zeros(1,64);IRSoftp=zeros(1,64); IRSofter==zeros(1,64); IRSofterp=zeros(1,64); fork=1:39   IRHard=IRHard+IRData(k,:)*DataHard(k); a=a+abs(DataHard(k));  IRSoft=IRSoft+IRData(k,:)*DataSoft(k); b=b+abs(DataSoft(k)); end fork=1:28   IRSoftp=IRSoftp+IRPilot(k,;)*PilotSort(k); c=c+abs  (PilotSoft(k)); end IRSoftp = IRSoft*Dat_Weight/b +IRSoftp   *(1−Dat_Weight)/c; IRHard = IRHard*Dat_Weight/a +IRPilotHard*(1−Dat_Weight); IRSoft = IRSoft*Dat_Weight/b +IRPilotHard*(1−Dat_Weight); %************ acq probability ************ a= IRPilotHard .* conj(IRPilotHard); for k=1:size(h1,2),[n,m]=max(a);h2(k)=m;a(m)=0;end c=0; for k=1:size(h1,2),forn=1:size(h1,2)     if(h2(k)==h1(n)), c=c+1; h2(k)=0; end   end, endAErrNoDFB = size(h1,2)−c; a = IRHard .* conj(IRHard); fork=1:size(h1,2),[n,m]=max(a);h2(k)=m;a(m)=0;end c =0; fork=1:size(h1,2),for n=1:size(h1,2)     if(h2(k)==h1(n)), c=c+1; h2(k)=0;end   end, end AErrHardDFB = size(h1,2)−c; a = IRSoft .* conj(IRSoft);for k=1:size(h1,2),[n,m]=max(a);h2(k)=m;a(m)=0;end c=0; fork=1:size(h1,2),for n=1:size(h1,2)     if(h1(k)==h1(n)), c=c+1; h2(k)=0;end   end, end AErrSoftDFB = size(h1,2)−c; a = IRSoftp .*conj(IrRSoftp); for k=1:size(h1,2),[n,m]=max(a);h2(k)=m;a(m)=0;end c=0;for k=1:size(h1,2), for n=1:size(h1,2)     if(h2(k)==h1(n)), c=c+1;h2(k)=0; end   end, end AErrSoftPDFB = size(h1,2)−c;AcqError(kkk,:)=AcqError(kkk,:)+...  [AErrNoDFB,AErrHardDFB,AErrSoftDFB, AErrSoftPDFB]   end  % nnn end       % kkk

1. A method of channel estimation in a cellular communication system inwhich symbols are transmitted between a mobile station and a basestation, the method comprising: receiving via a communication channel anincoming signal; providing a first estimate for the channel impulseresponse of that communication channel and utilising that first estimateto process the incoming signal to generate an estimated data symbol;using said estimated data symbol to generate a soft output feedbackdecision; and using the soft output feedback decision to make a furtherestimate of the channel impulse response.
 2. A method according to claim1, wherein the incoming signal incorporates symbols spread by aspreading code in a CDMA system.
 3. A method according to claim 2,wherein the channel impulse response is estimated by performing acorrelation process between a conjugate version of the spreading codeand the incoming signal, and multiplying the results of that process bythe soft feedback decision value as a weighting value for the channelimpulse response.
 4. A method according to any preceding claim, whereinthe incoming signal includes data symbols and pilot symbols, a uniquespreading code having been used respectively for pilot symbols and datasymbols.
 5. A method according to claim 2 or 4, in which a longspreading code has additionally been used to spread the symbols prior totransmission.
 6. A method of channel estimation in a cellularcommunication system in which symbols are transmitted between a mobilestation and a base station, the method comprising: receiving via acommunication channel an incoming signal which incorporates symbolsspread by a spreading code; providing a first estimate for the channelimpulse response of that communication channel and utilising that firstestimate to process the incoming signal to generate an estimated datasymbol; making a further estimate of the channel impulse response byperforming a correlation process between a conjugate version of thespreading code and the incoming signal, and multiplying the results ofthat process by a feedback decision based on said estimated data symbolas a weighting value for the channel impulse response.
 7. A methodaccording to claim 6, wherein the feedback decision is a soft output. 8.A method according to claim 6, wherein the feedback decision is a hardoutput.
 9. Circuitry for estimating a channel impulse response in acellular communication system in which symbols are transmitted between amobile station and a base station, the circuitry comprising: a receiverfor receiving via a communication channel an in coming signal whichincorporates symbols spread by a spreading code; a channel impulseresponse generator for providing a first estimate for the channelimpulse response of that communication channel; a data symbol generatorfor generating an estimated data symbol using the first estimate of thechannel impulse response; circuitry for providing a further estimate ofthe channel impulse response by performing a correlation process betweena conjugate version of the spreading code and the incoming signal, andmultiplying the results of that process by a feedback decision based onsaid estimated data symbol as a weighting value for the further estimateof the channel impulse response.
 10. Circuitry for estimating a channelin a cellular communication system in which symbols are transmittedbetween a mobile station and a base station, the circuitry comprising: areceiver for receiving an incoming signal via a communication channel; achannel impulse response generator for providing a first estimate forthe channel impulse response of that communication channel; a datasymbols generator for generating an estimated data symbol using thatfirst estimate; a soft output feedback decision generator for using saidestimated data symbol to generate a soft output feedback decision;wherein the soft output feedback decision is used to make a furtherestimate of the channel impulse response.